Independent component analysis based trial-to-trial variations reduction in fNIRS signal
- Resource Type
- Conference
- Authors
- Hu, Xiao-Su; Hong, Keum-Shik; Ge, Shuzhi Sam
- Source
- 2012 IEEE International Conference on Mechatronics and Automation Mechatronics and Automation (ICMA), 2012 International Conference on. :1429-1433 Aug, 2012
- Subject
- Robotics and Control Systems
Power, Energy and Industry Applications
Fields, Waves and Electromagnetics
Communication, Networking and Broadcast Technologies
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Hemodynamics
Spectroscopy
Fluctuations
Optical imaging
Brain
Humans
brain signal
functional near-infrared spectroscopy (fNIRS)
spontaneous low frequency hemodynamic fluctuation
trial-to-trial variability
- Language
- ISSN
- 2152-7431
2152-744X
Functional near-infrared spectroscopy (fNIRS) is emerging optical brain imaging technique. It measures the hemodynamic changes that effectively reflect the brain states. However, the fNIRS signal analysis is sensitive to the trial-to-trial variability (TTV), and the source of the TTV remains elusive. Previous functional magnetic resonance image (fMRI) study suggested that the TTV can be attributed to spontaneous low frequency hemodynamic fluctuation in fMRI signal. Meanwhile, recent fNIRS studies confirm that the spontaneous fluctuation in fNIRS signal can be robustly detected by functional near infrared spectroscopy (fNIRS). In this paper, we investigate the relationship between TTV and the spontaneous fluctuations in fNIRS signal. The subject is asked to complete a right finger tapping experiment. Independent component analysis as well as functional connectivity is used to reduce the TTV in the finger tapping experiment. The result suggests that the low frequency spontaneous fluctuation contribute significantly to the TTV in fNIRS signal.